TRADE VOLUME AND RETURN VOLATILITY IN ISTANBUL STOCK EXCHANGE

Abstract

This paper examines the relationship between trade volume and Istanbul Stock Exchange composite index ISE-100 return volatility for the period 1990-2008 by including the trade volume and the day of the week effect in to the GARCH, EGARCH and TGARCH models. The findings indicate the presence of the day of the week effect and leverage effect on return volatility. The estimation results of the GARCH and TGARCH models show that the effect of trade volume on return volatility is significant in the statistical sense but not positive. These findings provide strong evidence against the validity of Sequential Arrival Information and Mixed Distribution hypothesis in ISE

Keywords

• Trade Volume , Return Volatility , Day of the Week Effect , Conditional Heteroskedasticity Models

İSTANBUL MENKUL KIYMETLER BORSASI’NDA İŞLEM HACMİ VE GETİRİ VOLATİLİTESİ

Abstract

Bu çalışmada, işlem hacmi ve İstanbul Menkul Kıymetler Borsası bileşik endeks İMKB-100 getiri volatilitesi arasındaki ilişki, 1990-2008 dönemleri için GARCH, EGARCH ve TGARCH modellerine işlem hacmi ve haftanın günleri etkileri ilave edilerek araştırılmaktadır. Bulgular, getiri volatilitesinde haftanın günleri ve kaldıraç etkisinin var olduğuna işaret etmektedir. GARCH ve TGARCH modellerin tahmin sonuçları, işlem hacminin getiri volatilitesi üzerindeki etkisinin anlamlı olduğunu fakat pozitif olmadığını göstermektedir. Bu bulgular, İMKB’de “Ardışık Bilgi Akışı” ve “Karışık Dağılımlar” hipotezlerinin geçerliliğine aykırı kanıtlar sağlamaktadır.

Keywords

• İşlem Hacmi, Getiri Volatilitesi, Haftanın Günleri Etkisi, Koşullu Değişen Varyans Modelleri

References

1. AHMED, H.J.A., HASSAN, A., NASIR, A.M.D. (2005). The relationship between trading volume, volatility and stock market returns: a test of mixed distribution hypothesis for a pre and post crisis on Kuala Lumpur stock exchange. Investment Management and Financial Innovations. 3, 146-158. ss.
2. ANDERSEN, T.G. (1996). Return volatility and trading volume: An information flow interpretation of stochastic volatility. Journal of Finance. 51, 169-204. ss.
3. BAKLAVACI, H., KASMAN, A. (2006). An empirical analysis of trading volume and return volatility relationship in the Turkish Stock Market. Ege Academic Review. 6, 115-125. ss.
4. BLACK, F. (1976). Studies of stock price volatility changes. Proceedings of the 1976 meetings of the American Statistical Association. Business and Economics Statistics Section. Washington, DC: American Statistical Association, 177-181.ss.
5. BOLLERSLEV, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics. 31, 307-328. ss.
6. CLARK, P. (1973). A subordinated stochastic process model with finite variance for speculative prices. Econometrica. 91, 135-156. ss.
7. COPELAND, T. (1976). A model of asset trading under the assumption of sequential information arrival. The Journal of Finance. 31, 1149-1168. ss.
8. CORNELL, B. (1981). The relationship between volume and price variability in futures markets. The Journal of Futures Markets. 1, 303-316. ss.

9. EPPS, W., EPPS, M. (1976). The stochastic dependence of security price changes and transaction volumes: Implications for the mixture of distribution hypothesis. Econometrica. 44, 305-321. ss.
10. ESTEVE, V., L-LOPIS, J.S. (2005). Estimating the substitutability between private and public consumption: The case of Spain, 1960-2003. Applied Economics. 37, 2327-2334. ss.
11. FLOROS, C., VOUGAS, D.V. (2007). Trading volume and returns relationship in Greek stock index futures market: GARCH vs. GMM. International Research Journal of Finance and Economics. 12, 98-115. ss.
12. GLOSTEN, L.R., JAGANNATHAN, R., RUNKLE, D.E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance. 48, 1779-1801. ss.
13. GRAMMATIKOS, T., SAUNDERS, A. (1986). Future price variability: A test of maturity and volume effect. Journal of Business. 59, 319-330. ss.
14. HARRIS, L. (1983). The joint distribution of speculative prices and of daily trading volume. Working Paper. 34-84, Los Angeles: University of Southern California, Department of Finance and Business Economics.
15. HARRIS, L. (1984). Transactions data tests of the mixture of distributions hypothesis. Working Paper. 31-84, Los Angeles: University of Southern California, Department of Finance and Business Economics.
16. HARRIS, L. (1986). A transaction data study of weekly and intraday patterns in stock returns. Journal of Financial Economics. 16, 99-117. ss.
17. HARRIS, M., RAVIV, A. (1993). Differences of opinion make a horse race. Review of Financial Studies. 6, 479-506.ss.
18. JENNINGS, R.H., STARKS, L.T., FELLINGHAM, J.C. (1981). An equilibrium model of asset trading with sequential information arrival. Journal of Finance. 36, 143-161.ss.
19. KARPOFF, J.M. (1987). The relation between price changes and trading volume: A survey. Journal of Financial and Quantitative Analysis. 22, 109-126. ss.
20. LAMOUREUX, C.G., LASTRAPES, W.D. (1990). Heteroskedasticity in stock return data: Volume versus GARCH effects. Journal of Finance. 45, 221-229. ss.
21. MCKENZIE, M.D., FAFF, R.W. (2003). The determinants of conditional autocorrelation in stock returns. The Journal of Financial Research. 26, 259-274. ss.
22. MCMILLAN, D., SPEIGHT, A. (2002). Return-volume dynamics in UK futures. Applied Financial Economics. 12, 707-713. ss.
23. NELSON, D.B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica. 59, 347-370. ss.
24. NG, S., PERRON, P. (2001). Lag lenght selection and the construction of unit root tests with good size and power. Econometrica. 69, 1519-1554. ss.
25. PURI, T.N., PHILIPPATOS, G.C. (2008). Asymmetric volume-return relation and concentrated trading in LIFFE futures. European Financial Management. 14, 528-563. ss.
26. RAHMAN, S., LEE, C.F., ANG, K.P. (2002). Intraday return volatility process: Evidence from NASDAQ stocks. Review of Quantitative Finance and Accounting. 19, 155-180.
27. SHARMA, J.L., MOUGOUE, M., KAMATH, R. (1996). Heteroskedasticity in stock market indicator return data: Volume versus GARCH effects. Applied Financial Economics. 6, 337- 342. ss.
28. OGUM, G., BEER, F., NOUYRIGAT, G. (2004). An empirical analysis of Kenyan daily returns using EGARCH models. Frontiers in Finance and Economics. 1, 101-115. ss.
29. WORTHINGTON, A.C., HIGGS, H. (2003). Modelling the intraday return volatility process in the Australian equity market: An examination of the role of information arrival in S&P/ASX 50 stocks. Working Paper. 150, School of Economics and Finance, Queensland University of Technology.
30. YING, C.C. (1966). Stock market prices and volumes of sales. Econometrica. 34, 676-685. ss.
31. YÜKSEL, A. (2002). The performance of the Istanbul Stock Exchange during the Russian crisis. Emerging Markets Finance and Trade. 38, 78-99. ss.
32. ZAKOIAN, J.M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamic and Control. 18, 931-955. ss.